ascend-ai-codingascend-ai-coding/awesome-ascend-skills/skills/inference/ascend-migration-analysis/SKILL.mdascend-migration-analysis
Skill177 starsChanged 8 months agoNo licenceView on GitHub
通用 PyTorch 项目 Ascend NPU 迁移可行性分析。系统化扫描代码库中的 CUDA/GPU 依赖，按 7 大域分类评估（设备层、注意力机制、自定义算子、分布式通信、精度策略、第三方依赖、编译加速），并基于 Wan2.2 实际迁移经验提供逐项替代方案。适用于评估任何 DiT/Transformer 类模型（视频生成、LLM、多模态等）在昇腾 NPU 上的运行可行性与迁移工作量估算。
In this repository40 other files it gives its agents.
- AGENTS.mdAGENTS.md
- create-prSkill
- skill-creatorSkill
- gitcode-merge-flowSkill
- github-issue-rcaSkill
- github-issue-summarySkill
- tech-docs-guardSkill
- vllm-daily-pr-issue-trackerSkill
- ai-for-science-ai4s-mainSkill
- ai-for-science-ai4s-profilingSkill
- ascend-avi-vnpuSkill
- ascend-dmiSkill
- ascend-dockerSkill
- npu-docker-launcherSkill
- npu-smiSkill
- remote-npu-testSkill
- remote-server-guideSkill
- torch_npuSkill
- ais-benchSkill
- atc-model-converterSkill
- inferencex-reportSkill
- migration-ascend-torchnpu-skillsSkill
- npu-torchair-inferSkill
- vllm-ascend-serverSkill
- vllm-ascendSkill
- vllm-bench-serveSkill
- wan-ascend-adaptationSkill
- ascendcSkill
- ascend-oppluginSkill
- npu-op-benchmarkSkill
- triton-ascend-migrationSkill
- mindspeed-llm-train-profilerSkill
- mindspeed-mm-train-profilerSkill
- profiling-analysisSkill
- pytorch-profiling-collectionSkill
- training-mfu-calculatorSkill
- hccl-testSkill
- rl-msprobeSkill
- torch-npu-comm-testSkill
- verl-quickstartSkill
The file
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.